PeerCube: A Hypercube-Based P2P Overlay Robust against Collusion and Churn

Anceaume, Emmanuelle; Ludinard, Romaric; Ravoaja, Aina; Brasileiro, Francisco

doi:10.1109/saso.2008.44

Cited by 36 publications

(49 citation statements)

References 25 publications

(31 reference statements)

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“…Any structured graph proposed in the literature can be chosen. In this work we use PeerCube [16] essentially because each vertex of the hypercube gather from Smin to Smax nodes, which makes this cluster-based DHT highly robust to churn. Thus, in FixMe overlay as shown in Fig.…”

Section: Self-organizing Nodes In Dense Seedsmentioning

confidence: 99%

“…3, all the seeds are organized as follows. The first Smin nodes that are in a seed form the root of the hypercube, and upon new nodes arrivals, the dimension of the hypercube increases [16]. From the point of view of the neighboring seeds of any other seed s, only the root of the hypercube is visible.…”

Section: Self-organizing Nodes In Dense Seedsmentioning

confidence: 99%

“…In the former case, the cluster nodes simply update their view of the cluster. In the later case, Θ(log(H)) messages have to be sent to merge both clusters (See [16]). …”

Section: Proposition 4 (Cell Split)mentioning

confidence: 99%

“…As described in Section 4.3, a lookup operation is decomposed into three parts, namely, the hypercube traversal at the source of the lookup operation, the cells traversal and, the hypercube traversal at the destination of the lookup operation). As shown in [16], the dimension of an hypercube populated by H nodes equals to log(H/Smax). By setting Smax to log N , the number of messages required is equal to traverse an hypercube is equal to log(N D i=1 ρi)−log log N = O(log N ).…”

Section: Proposition 4 (Cell Split)mentioning

confidence: 99%

See 3 more Smart Citations

FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems

Anceaume

Merrer

Ludinard

et al. 2012

Lecture Notes in Computer Science

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Abstract. Monitoring a system is the ability of collecting and analyzing relevant information provided by the monitored devices so as to be continuously aware of the system state. However, the ever growing complexity and scale of systems makes both real time monitoring and fault detection a quite tedious task. Thus the usually adopted option is to focus solely on a subset of information states, so as to provide coarse-grained indicators. As a consequence, detecting isolated failures or anomalies is a quite challenging issue. In this work, we propose to address this issue by pushing the monitoring task at the edge of the network. We present a peer-to-peer based architecture, which enables nodes to adaptively and efficiently self-organize according to their "health" indicators. By exploiting both temporal and spatial correlations that exist between a device and its vicinity, our approach guarantees that only isolated anomalies (an anomaly is isolated if it impacts solely a monitored device) are reported on the fly to the network operator. We show that the end-to-end detection process, i.e., from the local detection to the management operator reporting, requires a logarithmic number of messages in the size of the network.

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Section: Self-organizing Nodes In Dense Seedsmentioning

confidence: 99%

Section: Self-organizing Nodes In Dense Seedsmentioning

confidence: 99%

“…In the former case, the cluster nodes simply update their view of the cluster. In the later case, Θ(log(H)) messages have to be sent to merge both clusters (See [16]). …”

Section: Proposition 4 (Cell Split)mentioning

confidence: 99%

Section: Proposition 4 (Cell Split)mentioning

confidence: 99%

See 2 more Smart Citations

FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems

Anceaume

Merrer

Ludinard

et al. 2012

Lecture Notes in Computer Science

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“…Our solution relies on the clusterized version of peer-topeer overlays combined with a mechanism that allows the enforcement of limited nodes lifetime. Clusterized versions of structured-based overlays [1,3] are such that clusters of nodes substitute nodes at the vertices of the graph. Nodes are grouped together according to some distance function.…”

mentioning

confidence: 99%

Brief Announcement: Induced Churn to Face Adversarial Behavior in Peer-to-Peer Systems

Anceaume

Brasileiro

Ludinard

et al. 2009

Lecture Notes in Computer Science

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StakeCube: Combining Sharding and Proof-of-Stake to Build Fork-Free Secure Permissionless Distributed Ledgers

2019

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Our work focuses on the design of a scalable permissionless blockchain in the proof-of-stake setting. In particular, we use a distributed hash table as a building block to set up randomized shards, and then leverage the sharded architecture to validate blocks in an efficient manner. We combine verifiable Byzantine agreements run by shards of stakeholders and a block validation protocol to guarantee that forks occur with negligible probability. We impose induced churn to make shards robust to eclipse attacks, and we rely on the UTXO coin model to guarantee that any stakeholder action is securely verifiable by anyone. Our protocol works against adaptive adversary, and makes no synchrony assumption beyond what is required for the byzantine agreement.

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PeerCube: A Hypercube-Based P2P Overlay Robust against Collusion and Churn

Abstract: Abstract

Cited by 36 publications

References 25 publications

FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems

FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems

Brief Announcement: Induced Churn to Face Adversarial Behavior in Peer-to-Peer Systems

StakeCube: Combining Sharding and Proof-of-Stake to Build Fork-Free Secure Permissionless Distributed Ledgers

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